Real-Time X-Ray-Based Facial Skeletal Identification

This research proposes a novel biometric identification framework that replaces conventional optical cameras with a real-time X-ray sensing system capable of capturing the internal skeletal structure of the human face. Unlike traditional face-recognition methods, which rely on external facial appearance, skin texture, lighting conditions, facial hair, cosmetic makeup, aging effects, or intentional visual modifications, this approach focuses on the underlying craniofacial bone geometry.

The core idea is to develop a unique radiographic facial-measurement model that extracts stable anatomical landmarks from the skull, such as orbital structure, nasal bone geometry, zygomatic arch configuration, jawline morphology, cranial proportions, and other measurable skeletal features. These measurements would be converted into a distinctive biometric signature representing the individual’s internal facial architecture.

Because the system is based on X-ray-visible skeletal patterns rather than surface appearance, it could be designed to be largely agnostic to external facial changes, including makeup, masks, facial swelling, cosmetic surface alterations, lighting variation, or changes in hairstyle and facial hair. The proposed framework would combine real-time radiographic imaging, anatomical landmark detection, geometric feature extraction, and AI-based matching against a secured biometric database.

The research objective is to investigate whether the human craniofacial skeleton can provide a reliable, stable, and uniquely identifiable biometric signature, enabling a new class of recognition systems based on internal facial morphology rather than external visual appearance. This concept may open new directions in forensic identification, high-security authentication, medical biometrics, and robust identity verification under conditions where conventional face-recognition systems are unreliable.